The<i>flamenco</i>Locus Controls the<i>gypsy</i>and<i>ZAM</i>Retroviruses and Is Required for Drosophila Oogenesis
Bibliographic record
Abstract
In Drosophila, the as yet uncloned heterochromatic locus flamenco (flam) controls mobilization of the endogenous retrovirus gypsy through the repeat-associated small interfering (rasi) RNA silencing pathway. Restrictive alleles (flamR) downregulate accumulation of gypsy transcripts in the somatic follicular epithelium of the ovary. In contrast, permissive alleles (flamP) are unable to repress gypsy. DIP1, the closest transcription unit to a flam-insertional mutation, was considered as a good candidate to be a gypsy regulator, since it encodes a dsRNA-binding protein. To further characterize the locus we analyzed P-induced flam mutants and generated new mutations by transposon mobilization. We show that flam is required somatically for morphogenesis of the follicular epithelium, the tissue where gypsy is repressed. This developmental activity is necessary to control gypsy and another retroelement, ZAM. We also show that flam is not DIP1, as none of the new permissive mutants affect the DIP1 coding sequence. In addition, two deletions removing DIP1 coding sequences do not affect any of the flamenco functions. Our results suggest that flamenco extends proximally to DIP1, spanning >130 kb of transposon-rich heterochromatin. We propose a model explaining the multiple functions of this large heterochromatic locus.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".